AI-enabled drones help farmers fight off pests, reduce food waste
Technology
AI helps farmers fight pests for more effective results
(Web Desk) - Researchers are looking for less labour and energy intensive ways to fight pests, and AI could help.
If the recent surge in artificial intelligence (AI) applications left you wondering whether the technology was limited to Silicon Valley’s alleys alone, then researchers at the University of Modena and Reggio Emilia in Italy have a pleasant surprise.
The research team used AI to help farmers fight pests and flew it on drones for more effective results.
Halyomorpha halys, known better by its common name the brown marmorated stink bug, is a major cause of headache for orchard owners in North America and southern Europe.
Estimates suggest that in Italy alone, this pest caused damages worth nearly US$ 640 million (588 million euros) in 2019 alone.
Conventional approaches, such as pheromone traps, visual sampling, and sweep-netting, are the only tools against the pest.
These approaches are labor-intensive and difficult to execute when dealing with large orchards.
The researchers, led by Lara Maistrello, an associate professor in the Department of Life Sciences at the University of Modena, sought methods that consumed less time and energy.
AI ON DRONES
The researchers developed an automated flight protocol so that drones could capture high-resolution images of pear orchards from a height of 26 feet (eight meters).
Drones flying at these heights were less disruptive to pest movements than human observers.
Interestingly, adult bugs also froze in response to a flying drone helping the camera pick high-resolution images of the site.
These images were then used to train AI models in identifying a pest infection.
Models trained using this data were more effective at spotting the stink bug with an accuracy of 97 percent compared to those trained from scratch.
The researchers suggest that the approach can be used for integrated pest management, including precise forecasting that can adapt to changing environmental and meteorological conditions.
